This episode explores the evolution of Java and its future in the context of emerging technologies like AI. The conversation begins with Josh Long recounting his experience at JavaOne 2025, highlighting the strong community aspect and the return of the event to the Bay Area. More significantly, the discussion pivots to Henri Tremblay's renowned JavaOne keynote, where he demonstrated the remarkable backward compatibility of Java by running Java code from the early days on a Windows 95 virtual machine, showcasing Java's "write once, run anywhere" capability. As the discussion progresses, they delve into the complexities and benefits of Java's module system, with Tremblay expressing some reservations about its impact on developers. For instance, the challenges of migrating legacy applications and the difficulties in using reflection are highlighted. Against this backdrop, the conversation shifts to the exciting advancements in the JVM, including Project Valhalla's value types, which promise significant performance improvements by reducing heap allocations and improving cache locality. This is further amplified by the discussion of the Vector API, which allows for leveraging specialized hardware for enhanced performance in computationally intensive tasks. Finally, the podcast touches upon the integration of AI into Java applications, with Spring AI providing support for AI engineering patterns, and the potential for Java to play a significant role in the future of AI development, particularly in the area of model inference. What this means for the future of Java development is a vibrant ecosystem constantly adapting to new technologies while retaining its core strengths of backward compatibility and performance.
